Results 21 to 30 of about 8,161,576 (257)
On universal transfer learning [PDF]
Theoretical Computer Science, 2007 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Impact of intercity low-carbon technology transfer on carbon emission reduction in China:Based on the “dichotomy” of knowledge learning and technology learning [PDF]
Ziyuan Kexue, 2023 [Objective] Increasing the transfer of low-carbon technology (LCT) is the key to narrowing the gap in LCT between regions and improving the overall level of low-carbon technology of China.
SHANG Yongmin, MI Zefeng, ZHOU Can, LIN Lan
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Inteligencia Artificial, 2022 Deep Learning and transfer learning models are being used to generate time series forecasts; however, there is scarce evidence about their performance prediction that it is more evident for monthly time series.
Martín Solís +1 more
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Transfer Learning in Magnetic Resonance Brain Imaging: A Systematic Review
Journal of Imaging, 2021 (1) Background: Transfer learning refers to machine learning techniques that focus on acquiring knowledge from related tasks to improve generalization in the tasks of interest.
Juan Miguel Valverde +6 more
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Factors influencing the learning transfer of nursing students in a non-face-to-face educational environment during the COVID-19 pandemic in Korea: a cross-sectional study using structural equation modeling [PDF]
Journal of Educational Evaluation for Health Professions, 2023 Purpose The aim of this study was to identify factors influencing the learning transfer of nursing students in a non-face-to-face educational environment through structural equation modeling and suggest ways to improve the transfer of learning.
Geun Myun Kim +2 more
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Artificial Intelligence, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Peilin Zhao +3 more
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Komputika, 2023 Deep learning is a branch of machine learning with many highly successful applications. One application of deep learning is image classification using the Convolutional Neural Network (CNN) algorithm. Large image data is required to classify images with
Muhammad Daffa Arviano Putra +4 more
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Fuzzy Inference and Manifold Regularization Combined Feature Transfer Learning
Jisuanji kexue yu tansuo, 2020 Transfer learning leverages the rich data in the source domain to provide support for building accurate models in the target domain. Feature transfer learning is a kind of widely studied technology in transfer learning, but the existing feature transfer ...
SONG Yixuan, DENG Zhaohong, QIN Bin
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Limits of Transfer Learning [PDF]
, 2020 Transfer learning involves taking information and insight from one problem domain and applying it to a new problem domain. Although widely used in practice, theory for transfer learning remains less well-developed. To address this, we prove several novel results related to transfer learning, showing the need to carefully select which sets of ...
Jake Williams +4 more
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Frontiers in Psychology, 2017 The current experiment investigated generalizability of motor learning in proximal versus distal effectors in upper extremities. Twenty-eight participants were divided into three groups: training proximal effectors, training distal effectors, and no ...
Tore K. Aune +3 more
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